JournAI.

What happens when our experience, expertise, and intelligence become the very things limiting what we can see?

I’ve been observing something interesting in the way people interact with AI. We seem perfectly comfortable with technology becoming more capable, as long as it doesn’t challenge our perception of our own capabilities. We love discovering that AI can do something we couldn’t do before. But when it starts doing something we’ve spent years becoming good at, the reaction can be very different.

Suddenly, we’re less impressed. We start explaining why the output isn’t good enough. Why it doesn’t understand the finer points. Why human experience cannot be replaced. And sometimes, we’re absolutely right.

But I wonder how often we’re genuinely evaluating the technology, and how often we’re protecting something about ourselves. Because AI is creating a rather uncomfortable situation. For perhaps the first time in our professional lives, the things we’ve spent years learning are becoming accessible to people who haven’t invested those years.

And I think our ego has quite a lot to say about that.

The uncomfortable experience of becoming a beginner again

There’s something particularly uncomfortable about being highly competent in your field and suddenly finding yourself completely inexperienced in something that could change how your field operates.

You’ve spent years building your expertise. You know how things work. People come to you for advice. You can recognise problems before others even notice them. And then you encounter AI.

Suddenly, you don’t understand the terminology. You don’t know which tools to use. Someone with a fraction of your professional experience is showing you how to accomplish things you didn’t even know were possible. You find yourself asking basic questions. And perhaps the most uncomfortable part is that your previous experience doesn’t automatically make you good at this.

I’ve noticed how quickly we can become defensive in these situations:

• “It’s too technical.”
• “I don’t need all of that for my business.”
• “My work is different.”
• “AI will never understand what I do.”

Sometimes those statements are completely valid. But sometimes they’re convenient conclusions that allow us to remain exactly where we are. Because learning something new requires us to temporarily give up the comfort of being competent - and the more experienced we become, the less accustomed we are to that feeling.

We say we value learning, but how comfortable are we with being visibly inexperienced? It’s an interesting contradiction. We admire beginners for their curiosity, yet often expect ourselves to approach every new subject with the confidence of an expert.

AI is exposing that contradiction rather quickly.

Our imagination is still shaped by our old limitations

I think this is one of the most underestimated consequences of technological progress. We don’t only organise our work around what we know. We organise our imagination around it, too.

If you’ve spent ten years running a business without technical skills, you’ve probably learned to think within that limitation. You don’t imagine building your own software because you’ve never been able to. You don’t consider certain business models because they would require a team you can’t afford. You don’t explore particular ideas because you already know how expensive or complicated they would be to execute.

Eventually, you stop questioning those limitations. They become part of how you understand your business.

Then technology changes. Suddenly, you can build a functional prototype without knowing how to code. You can connect systems that previously required technical assistance. You can experiment with ideas that would once have required a significant investment. Of course, these capabilities still have limitations, and building something reliable requires understanding, testing, and judgment. But the conditions have changed.

And here’s what I find fascinating. We can have access to entirely new capabilities and still make decisions as though we don’t. We continue planning our businesses around constraints that may no longer apply. We keep solving problems the same way because we haven’t considered that the problem itself could now be approached differently.

And when someone suggests a new possibility, our first instinct may be to explain why it won’t work. Based on what we know. Based on our experience. Based on the very limitations that shaped our thinking in the first place.

Which brings me to another uncomfortable thought.

Sometimes our expertise becomes the limitation

Experience is incredibly valuable. It helps us recognise patterns, make decisions, avoid mistakes, and understand complexities that beginners cannot yet see. But experience also creates expectations. We develop strong ideas about how things work, how long they take, what they cost, and what’s realistically possible. And after years of being right about those things, we become quite attached to our conclusions.

Imagine someone who has spent fifteen years developing websites. They understand the technical complexity, the architecture, the testing, the maintenance. Then someone with no programming background builds a working prototype using AI in an afternoon. The experienced developer immediately sees everything that’s missing. And they’re probably right.

But here’s the interesting question. Are they evaluating what the person has actually accomplished, or comparing it to everything they know a production-ready application requires? Those are two different evaluations. One recognises that a beginner has gained a capability they didn’t previously have. The other measures that capability against the standards of an entirely different task.

Both perspectives matter. But when we automatically apply the second, we can miss the significance of the first. The beginner hasn’t become an experienced developer - but they can now do something they couldn’t do before. And that changes their options.

I see a similar pattern in business. We sometimes use our expertise to explain why something is difficult before exploring whether the difficulty has changed. We know too much about how things used to work to easily imagine how differently they might work now.

Our experience can help us recognise what’s possible. It can also make us exceptionally good at explaining why something isn’t. The challenge is knowing when to trust our experience and when to question the assumptions behind it.

AI is challenging our need to be the one who knows

There’s another part of professional identity that AI is beginning to challenge: our relationship with being the person who has the answers.

For many of us, expertise comes with a certain position. We’re the ones people consult. We solve problems. We explain things. We know what to do. And being that person feels good. There’s nothing inherently wrong with that - competence deserves recognition.

But what happens when knowing the answer becomes less scarce? When a client can independently explore a problem that previously required your consultation? When a junior colleague can generate an analysis that would once have taken you hours? When someone without your background can produce a reasonable first solution? Does that diminish your expertise - or does it simply change where your expertise becomes valuable?

I think this is where things become particularly interesting. Because we can respond by trying to prove how much more we know. We can focus on everything AI gets wrong. We can emphasise the years of experience that technology doesn’t have. And sometimes those distinctions are essential. But we can also become so invested in demonstrating our superiority that we overlook what the technology could help us accomplish.

When being the person who knows becomes part of our identity, discovering that we don’t know something can feel like losing something. And that can make curiosity surprisingly difficult.

I wonder how many opportunities we dismiss because exploring them would require us to admit that someone, or something, knows something we don’t. How many questions we don’t ask because they seem too basic. How many experiments we avoid because we might not be immediately good at them. How much energy we spend protecting our existing competence instead of expanding it.

What are we actually protecting?

I don’t think our ego is necessarily threatened by AI itself. I think it’s threatened by what AI reveals about some of the things we’ve been using to define ourselves - that being experienced doesn’t mean we’re always right. That being highly skilled doesn’t mean the way we work is still the best way. That knowing more than someone else doesn’t necessarily mean we can see more possibilities. And that years of effort don’t guarantee that a particular task will remain difficult or valuable in the same way.

These are uncomfortable ideas. Especially for those of us who have spent years building businesses, developing expertise, and becoming independent through our own knowledge and abilities. But there’s something almost ironic about defending those achievements by refusing to explore the very technology that could expand them.

We worked hard to become capable. Why would we want our capabilities to stop growing at the boundaries of what we already know?

Perhaps the most useful thing we can do is become a little less attached to being the expert in every situation. To allow ourselves to ask questions we think we should already know the answers to. To recognise that something can be imperfect and still represent an important new possibility. To reconsider a limitation without feeling that we’re invalidating the years we spent working around it. And to become curious when someone with less experience accomplishes something we didn’t expect.

Because perhaps the most interesting question isn’t whether AI can do what we do. It’s how much more we might be capable of if we stopped needing our existing knowledge to define the limits of what’s possible.

And I think that’s a question worth sitting with. Not only as professionals, but as people who have spent years becoming very good at being who we already are.

The pitch is always time. Every tool, every demo, every headline: this will save you hours.

It’s true. It saves me hours. Some days a lot of them - a research pass that would have eaten an afternoon, a first draft that would have taken all morning, a spreadsheet cleaned while I make coffee. The hours are real. I can feel them arrive.

Then I watch what I do with them, and it is almost always the same thing. I make more.

Another piece of content, because the draft came so easily. Another project opened, because the setup that used to take a week now takes an evening. Another idea tested, because testing is cheap now. A thing that was already fine, polished again, because I can. Work I hadn’t planned to take, taken - why not, it’s faster now. I don’t stop at the edge of the saved time and rest inside it. I refill it, immediately, with more building.

And here is the part I keep turning over: I’m not doing this because I’m disciplined, or driven. I’m doing it because it feels good. There is a specific pleasure in describing an idea in two sentences and watching it become a working thing before the coffee is cold. That loop - think it, build it, see it - is one of the best feelings in this work. The tools didn’t only remove the friction. They made the making itself more fun. So of course I do more of it.

Which means the saved time was never really free time. It was capacity. And capacity, it turns out, is not the same gift as freedom.

Freedom would be the afternoon that stays empty. Capacity is an afternoon with room for three more things in it. The tools gave me the second one and let me call it the first.

I used to think the constraint on my business was how much I could produce. For years that was true - there were only so many hours, so the hours decided what got made. AI quietly removed that constraint, and I expected to feel lighter. Mostly I feel the opposite pull. Now that I can make almost anything quickly, the question of what is actually worth making has nowhere left to hide. The limit moved. It used to be how much I can produce. Now it is how much I am willing to carry.

I don’t have this solved. I’m writing it down because I’m in the middle of it, not on the other side. I still open the new project. I still polish the thing that was fine. Some of that is real work and some of it is the dopamine wearing a work costume, and honestly, in the moment, I can’t always tell which.

The tools promised to give me my time back. They did. I just haven’t decided yet whether getting it back means anything - if the first thing I do with it is hand it straight to the work.